Abstract/Summary:

Particulate pollution-driven severe haze events in Southeast Asia have become more intense and frequent in recent years, degrading air quality and threatening human health. While widespread biomass burning is a major source of these events, particulate pollutants from other human activities also play a key role in degrading the region’s air quality. In this study, MIT Joint Program and collaborating researchers conducted numerical simulations to examine the contributions of aerosols emitted from fire (via biomass burning) vs. non-fire (including fossil fuel combustion, road and industrial dust, land use and land-use change) sources to the degradation of air quality and visibility over Southeast Asia. Covering 2002-2008, these simulations were driven by emissions from: (a) fossil fuel burning only, (b) biomass burning only, and (c) both (a) and (b).

Across the ASEAN 50 cities, these model results reveal that 39% of observed low visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20% by fossil fuel burning alone, a further 8% by biomass burning alone, and a further 5% by a combination of fossil fuel and biomass burning. The remaining 28% of observed LVDs remain unexplained, likely due to emissions sources not yet identified.

Further analysis of the 24-hour PM2.5 Air Quality Index (AQI) indicates that compared to the simulated result of the standalone non-fire emissions case, the coexisting fire and non-fire PM2.5 case can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23% to 34%. The premature mortality among major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ~4110 per year in 2002 to ~6540 per year in 2008.

Finally, the study includes an exploratory experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore. All results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia must consider controlling emissions from non-fire anthropogenic sources.

Abstract/Summary:

Particulate pollution-driven severe haze events in Southeast Asia have become more intense and frequent in recent years, degrading air quality and threatening human health. While widespread biomass burning is a major source of these events, particulate pollutants from other human activities also play a key role in degrading the region’s air quality. In this study, MIT Joint Program and collaborating researchers conducted numerical simulations to examine the contributions of aerosols emitted from fire (via biomass burning) vs. non-fire (including fossil fuel combustion, road and industrial dust, land use and land-use change) sources to the degradation of air quality and visibility over Southeast Asia. Covering 2002-2008, these simulations were driven by emissions from: (a) fossil fuel burning only, (b) biomass burning only, and (c) both (a) and (b).

Across the ASEAN 50 cities, these model results reveal that 39% of observed low visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20% by fossil fuel burning alone, a further 8% by biomass burning alone, and a further 5% by a combination of fossil fuel and biomass burning. The remaining 28% of observed LVDs remain unexplained, likely due to emissions sources not yet identified.

Further analysis of the 24-hour PM2.5 Air Quality Index (AQI) indicates that compared to the simulated result of the standalone non-fire emissions case, the coexisting fire and non-fire PM2.5 case can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23% to 34%. The premature mortality among major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ~4110 per year in 2002 to ~6540 per year in 2008.

Finally, the study includes an exploratory experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore. All results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia must consider controlling emissions from non-fire anthropogenic sources.